How to Improve Data Labeling Efficiency
with Auto-Labeling, Uncertainty Estimates,
and  Active Learning 

Auto-Label AI, although extremely powerful, cannot always be 100% accurate. Which is exactly why you need to measure and evaluate how much you can trust the model output when utilizing auto labeling for data annotation.

In this whitepaper, we dive into the machine learning theory and techniques that were developed to evaluate our auto-labeling AI. More specifically, how the platform estimates the uncertainty of auto-labeled annotations and applies it to active learning.

Free Whitepages Download Form

By submitting your information, you agree to Superb AI's Terms of Service and Privacy Policy. You can opt out anytime.
A check mark
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.